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A unified model for regularized and robust portfolio optimization

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  • Plachel, Lukas

Abstract

Mean-variance optimization severely suffers from model- and estimation errors. Two commonly isolated but complementary concepts to overcome the corresponding limitations are problem regularization and robustification. I introduce a joint method for covariance regularization and robust optimization which exploits this complementarity and I show that both the regularization- as well as the robust optimization part can be achieved through systematic manipulations of the correlation matrix’ eigenvalues. An application of the method to equity markets reveals similarly attractive behavior as pure covariance regularization during normal times and improved performance if a jump in systematic risk occurs. Furthermore, the model constitutes a framework for the logically consistent incorporation of systematic risk expectations into the portfolio selection problem and thereby complements similar models for individual return expectations, such as the Black and Litterman model.

Suggested Citation

  • Plachel, Lukas, 2019. "A unified model for regularized and robust portfolio optimization," Journal of Economic Dynamics and Control, Elsevier, vol. 109(C).
  • Handle: RePEc:eee:dyncon:v:109:y:2019:i:c:s0165188919301769
    DOI: 10.1016/j.jedc.2019.103779
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    Cited by:

    1. Panos Xidonas & Ralph Steuer & Christis Hassapis, 2020. "Robust portfolio optimization: a categorized bibliographic review," Annals of Operations Research, Springer, vol. 292(1), pages 533-552, September.
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    3. Bian, Zhicun & Liao, Yin & O’Neill, Michael & Shi, Jing & Zhang, Xueyong, 2020. "Large-scale minimum variance portfolio allocation using double regularization," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).
    4. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2021. "Robust Portfolio Selection Problems: A Comprehensive Review," Papers 2103.13806, arXiv.org.

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    More about this item

    Keywords

    Covariance regularization; Robust optimization; Portfolio selection;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G01 - Financial Economics - - General - - - Financial Crises
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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